Blended intelligence of FCA with FLC for knowledge representation from clustered data in medical analysis

Formal concept analysis is the process of data analysis mechanism with emergent attractiveness across various fields such as data mining, robotics, medical, big data and so on. FCA is helpful to generate the new learning ontology based techniques. In medical field, some growing kids are facing the problem of representing their knowledge from their gathered prior data which is in the form of unordered and insufficient clustered data which is not supporting them to take the right decision on right time for solving the uncertainty based questionnaires. In the approach of decision theory, many mathematical replicas such as probability-allocation, crisp set, and fuzzy based set theory were designed to deals with knowledge representation based difficulties along with their characteristic. This paper is proposing new ideological blended approach of FCA with FLC and described with major objectives: primarily the FCA analyzes the data based on relationships between the set of objects of prior-attributes and the set of attributes based prior-data, which the data is framed with data-units implicated composition which are formal statements of idea of human thinking with conversion of significant intelligible explanation. Suitable rules are generated to explore the relationship among the attributes and used the formal concept analysis from these suitable rules to explore better knowledge and most important factors affecting the decision making. Secondly how the FLC derive the fuzzification, rule-construction and defuzzification methods implicated for representing the accurate knowledge for uncertainty based questionnaires. Here the FCA is projected to expand the FCA based conception with help of the objective based item set notions considered as the target which is implicated with the expanded cardinalities along with its weights which is associated through the fuzzy based inference decision rules. This approach is more helpful for medical experts for knowing the range of patient’s memory deficiency also for people whose are facing knowledge explorer deficiency

Abstract economic modeling : a semantic-philosophical definition of economic models

As fundações análogas das ideias de Kuhn e da visão pragmática das teorias favorecem uma união de pensamentos. Na concepção de Kuhn após a Estrutura das Revoluções Científicas, a filosofia da linguagem – especialmente as teorias de uso da linguagem – e suas ramificações nas ciências cognitivas são formas efetivas de julgar problemas científicos. Baseados nessas novas ideias, os interpretes de Kuhn propuseram a teoria psicológica dos Enquadramentos Dinâmicos como uma forma funcional de reavaliar a evolução científica. Uma aplicação dessa teoria para reler as definições pragmáticas de modelos foi realizada nessa dissertação, expondo a incomparabilidade entre estudos de caso, o que impede o avanço das discussões. Consequentemente, a criação de definições comparáveis é necessária para o desenvolvimento dos debates pragmáticos. Inspirada em Sugden (2000;2009), a solução proposta foi a criação de paradigmas plausíveis. Seguindo esta linha de raciocínio, um exame da história do pensamento econômico foi realizado buscando uma fundação crível para a definição de modelos econômicos abstratos. A pesquisa identificou os trabalhos de Tinbergen (1935) e de Von Neumann (1945) como os primeiros a usarem o termo ‘modelo’ em sentido abstrato e, portanto, como uma fundação sólida para um paradigma definidor do termo modelo econômico no período que transcorre de 1930 à 1950. Em seguida, a combinação da teoria dos Enquadramentos Dinâmicos e dos exemplares resultou na definição de modelos econômicos contendo cinco características: adaptabilidade, neutralidade, estrutura matemática, simplificação e objetivo. Uma avaliação subsequente da disseminação do termo de 1930 até 1950 sugere que os exemplares escolhidos são uma fundação plausível, ainda que a definição não tenha sido instantânea nem completamente disseminada entre os economistas.The analogous foundations of Kuhnian ideas and of The Pragmatic View of Theories favor a union of thoughts. In Kuhn’s renewed ideas, philosophy of language – especially use theories - and its ramifications in cognitive sciences are an effective form of judging scientific conundrums. Based on this insight, Kuhn’s interpreters proposed the psychological theory of Dynamic Frames as a functional form of reviewing scientific evolution. An application of Dynamic Frames was realized to reread pragmatic definitions of models, exposing the incomparability between case-studies, which hampers the development of discussions. Consequently, the creation of comparable definitions is necessary for the advancement of pragmatic debates. Inspired by Sugden (2002; 2009), the proposed solution was the creation of plausible paradigms. Following this mode of reasoning, an examination of history of economic thought was realized searching for a credible foundation for the definition of abstract economic models. The exploration suggested Tinbergen’s (1935) and Von Neumann’s (1945) works as the first ones to use the term “model” in an abstract sense and thus as a solid foundation for a paradigm intended to define economic models. The following combination of Dynamic Frames ideas and the exemplars resulted in a definition of models containing five characteristics: adaptability; neutrality; mathematical structure; simplification; and objective. A subsequent examination of the dissemination of the term from 1930s to 1950s suggested the exemplars were a plausible foundation, even though the definition was neither instantly nor completely disseminated among economists

Talking Nets: A Multi-Agent Connectionist Approach to Communication and Trust between Individuals

A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents’ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Grice’s (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions